July 31, 2016

Notes on Spark and Databricks — technology

During my recent visit to Databricks, I of course talked a lot about technology — largely with Reynold Xin, but a bit with Ion Stoica as well. Spark 2.0 is just coming out now, and of course has a lot of enhancements. At a high level:

The majority of Databricks’ development efforts, however, are specific to its cloud service, rather than being donated to Apache for the Spark project. Some of the details are NDA, but it seems fair to mention at least:

Two of the technical initiatives Reynold told me about seemed particularly cool. One, on the machine learning side, was a focus on training models online as new data streams in. In most cases this seems to require new algorithms for old model types, with a core idea being that the algorithm does a mini gradient descent for each new data point.

The other cool idea fits the trend of alternatives to the “lambda architecture”. Under the name “structured streaming”, which seems to be a replacement for “DStreaming”, the idea is to do set-based SQL processing even though membership of the set changes over time. Result sets are extracted on a snapshot basis; you can keep either all the results from each snapshot query or just the deltas.

Despite all this, there’s some non-trivial dissatisfaction with Spark, fair or otherwise.

To the last point, I raised one of the biggest specifics with Reynold, namely Spark’s lack of a strong built-in data persistence capability. Reynold’s answer was that they’re always working to speed up reading and writing from other forms of persistent storage. E.g., he cited a figure of ~100 million rows/core/second decoded from Parquet.

Comments

3 Responses to “Notes on Spark and Databricks — technology”

  1. Notes on Spark and Databricks — generalities | DBMS 2 : DataBase Management System Services on July 31st, 2016 10:31 am

    […] shall explain below. I also am posting separately about Spark evolution, especially Spark 2.0. I’ll also talk a bit in that post about Databricks’ […]

  2. Notes from a long trip, July 19, 2016 | DBMS 2 : DataBase Management System Services on August 7th, 2016 1:28 pm

    […] and Databricks are both prospering, and of course enhancing their technology as […]

  3. “Real-time” is getting real | DBMS 2 : DataBase Management System Services on September 6th, 2016 1:09 pm

    […] models at interactive speeds is often easy. Retraining them quickly is much harder, and at this point only rarely […]

Leave a Reply




Feed: DBMS (database management system), DW (data warehousing), BI (business intelligence), and analytics technology Subscribe to the Monash Research feed via RSS or email:

Login

Search our blogs and white papers

Monash Research blogs

User consulting

Building a short list? Refining your strategic plan? We can help.

Vendor advisory

We tell vendors what's happening -- and, more important, what they should do about it.

Monash Research highlights

Learn about white papers, webcasts, and blog highlights, by RSS or email.